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masha68 [24]
3 years ago
15

16d - (4 - 5d) = -67 Please help me find d

Mathematics
2 answers:
san4es73 [151]3 years ago
6 0
The negative at the other side of the parenthesis must be distributed inside the parenthesis changing the equation to 16d -4 + 5d = -67.

now add any like terms. in this equation that would be 16d + 5d = 21d 

now the equation vhanges too 21d - 4 = -67 

now you isolate the variable. so add 4 to both sides of the equal sign 
21d - 4 (+4) = -67 (+4) 

21d =  - 63

divide by 21 on both side of equal sign 21d(/21) = -63 (/21) 

d= -3
madreJ [45]3 years ago
5 0
16d-(4-5d)=-67\\\\16d-4-(-5d)=-67\\\\16d-4+5d=-67\\\\21d-4=-67\ \ \ \ /+4\\\\21d-4+4=-67+4\\\\21d=-63\ \ \ \ /:21\\\\21d:21=-63:21\\\\d=-3
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Step-by-step explanation:

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− 12 /49

y-intercept:  

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What is the slope of the line?
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6m - 8 = 2 + 9m - 1 Show your work and answer.
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6m-8 = 2+9m-1

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4 years ago
Calculate the sample variance and sample standard deviation for the following frequency distribution of heights in centimeters f
Zolol [24]

Answer:

\bar X = \frac{\sum_{i=1}^n X_i f_i}{n}= \frac{22026.1}{171}=128.81

s^2 = \frac{2839948.85- \frac{(22026.1)^2}{171}}{171-1}= 16.59

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Step-by-step explanation:

For this case we can calculate the sample variance and deviation with the following table

Class               Midpoint (Xi)    fi        Xi*fi       Xi^2 *fi

120.6-123.6        122.1             17      2075.7   253443

123.7-126.7        125.2            49      6134.8    768077

126.8-129.8        128.3            29     3720.7    477365.8

129.9-132.9        131.4             41       5387.4   707904.4

133.0-136.0        134.5            35      4007.5   633158.8

___________________________________________

Total                                        171   22026.1    2839948.85

For this case we can calculate the mean or expected value with the following formula:

\bar X = \frac{\sum_{i=1}^n X_i f_i}{n}= \frac{22026.1}{171}=128.81

Now we can calculate the sample variance with the following formula:

s^2 =\frac{\sum f_i X^2_i -[\frac{(\sum X_i f_i)}{n}]^2}{n-1}

And if we replace we got:

s^2 = \frac{2839948.85- \frac{(22026.1)^2}{171}}{171-1}= 16.59

And the standard deviation would be the square root of the variance and we got:

s= \sqrt{16.59}=4.07

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